Defining a Cloud Native Approach to Integration

Timm Wilson
Timm Wilson
Feb 24, 2021
Defining a Cloud Native Approach to Integration
Defining a Cloud Native Approach to Integration

Application integration is as old as the hills - as old as apps themselves. In the beginning, monolithic apps achieved de facto integration by virtue of their tight coupling of all services.

Figure 1: Ye Olde Monolith

Of course, we all know how the story goes - microservices and containers allow different parts of an app to be upgraded independently, which supports faster response to customer needs, faster feature delivery, better uptime, support for smaller teams to focus on different parts of the stack, etcetera.

So, where does this leave application integration?

Can/should enterprises stick with yesterday’s message-based solutions?

It’s not necessarily wrong to do so. Just like it’s not necessarily *wrong* to stick with a monolithic app. But you do forgo some important benefits.

Message-based integration tools suffer from the same tight coupling that simplifies, but also inherently limits, monolithic apps. These legacy integration tools include the payload with the integration message, which means the integration platform needs to understand a lot about the integration source app and the integration target app. Fine for one static integration, sure.

But what happens when you want to add another target to an existing integration?

You have to create a new integration. Over time, the term spaghetti will come to mind. And we all know what a high carb diet does to waistlines-of-code.  

Cloud native integration technology, which is based on event-driven architecture (EDA), surpasses simple message-oriented integration. Like its predecessor, the cloud native approach also produces, detects, consumes, and reacts to events. Importantly, events differ from messages in that events are simply a notification that a change in state (e.g., for sale/sold, working/not working) has occurred. 

In a cloud native EDA integration, publishers of events do not need to know their subscribers. In this modern model, event consumers decide which event sources they are interested in. The EDA enables a constant state of awareness so that producers can ‘stream’ data about various types of events (or topics) in real time to all potential consumers. And since it’s cloud native, all this power comes in a portable, lean, agile, scale-to-zero package. 

Figure 2: Cloud Native Integration Pairs Well with Real-time Event Streaming

TriggerMesh helps the central DevOps team at a Fortune 500 bank automate code governance as a service for the entire enterprise, reducing code auditing time from days to minutes. The solution marries cloud native integration with Apache Kafka to power the real-time enterprise. 

Grab this quick 451 Research report “Integration in Cloud-Native Architecture: An Event-Driven Approach” for a look at how real-time cloud native integration can power up your agility.





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